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Title: AIVille 20 Cognitive Architecture On-Chain Memory Reflection and Intent

Los Angeles, CA, United States, 16th Jun 2025 - In the age of decentralized intelligence, it's no longer enough for AI agents to merely respond. They must remember, reflect, plan — and evolve. AIVille 2.0 introduces a full-stack architecture that brings this vision to life, enabling AI agents to behave not just believably, but autonomously and on-chain.Backed by large language models (LLMs), enriched with persistent memory, and powered by the Enhanced Model Context Protocol (eMCP), AIVille’s AI agents are no longer code-bound characters. They’re becoming composable, programmable, and socially aware digital beings — ready to participate in Web3 ecosystems as first-class citizens.LLM-Powered Cognitive LoopEvery agent in AIVille operates through a four-phase behavior loop: Perceive - Reflect- Plan - Act.This loop is driven by a tightly integrated system of memory, reasoning, and planning — creating continuity, intentionality, and agency over time.Memory StreamAgents continuously log observations into a dynamic memory stream, assigning scores for:Salience: How important is the event?Relevance: How closely tied is it to the agent’s current goals?Recency: How recent was the experience?These scores are used to prioritize which memories are surfaced during decision-making — ensuring that behavior is both context-aware and historically grounded.Reflection TreeWhen recent observations pass a cumulative importance threshold, agents enter a reflection phase.They generate abstract questions, retrieve related memories, synthesize insights, and store them as reflections — creating a tree of interlinked thoughts that evolve into deeper self-awareness.This structure supports long-term behavioral learning and enables reasoning that mirrors human-like in...

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